<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maillo, Alberto</style></author><author><style face="normal" font="default" size="100%">Huergo, Estefania</style></author><author><style face="normal" font="default" size="100%">Apellániz-Ruiz, María</style></author><author><style face="normal" font="default" size="100%">Urrutia-Lafuente, Edurne</style></author><author><style face="normal" font="default" size="100%">Miranda, María</style></author><author><style face="normal" font="default" size="100%">Salgado, Josefa</style></author><author><style face="normal" font="default" size="100%">Pasalodos-Sanchez, Sara</style></author><author><style face="normal" font="default" size="100%">Delgado-Mora, Luna</style></author><author><style face="normal" font="default" size="100%">Teijido, Óscar</style></author><author><style face="normal" font="default" size="100%">Goicoechea, Ibai</style></author><author><style face="normal" font="default" size="100%">Carmona, Rosario</style></author><author><style face="normal" font="default" size="100%">Perez-Florido, Javier</style></author><author><style face="normal" font="default" size="100%">Aquino, Virginia</style></author><author><style face="normal" font="default" size="100%">López-López, Daniel</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Beltran, Sergi</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Lasa, Iñigo</style></author><author><style face="normal" font="default" size="100%">Beloqui, Juan José</style></author><author><style face="normal" font="default" size="100%">Alonso, Ángel</style></author><author><style face="normal" font="default" size="100%">Gomez-Cabrero, David</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterization of the Common Genetic Variation in the Spanish Population of Navarre.</style></title><secondary-title><style face="normal" font="default" size="100%">Genes (Basel)</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genes (Basel)</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Frequency</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetics, Population</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Genome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 May 04</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">15</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Large-scale genomic studies have significantly increased our knowledge of genetic variability across populations. Regional genetic profiling is essential for distinguishing common benign variants from disease-causing ones. To this end, we conducted a comprehensive characterization of exonic variants in the population of Navarre (Spain), utilizing whole genome sequencing data from 358 unrelated individuals of Spanish origin. Our analysis revealed 61,410 biallelic single nucleotide variants (SNV) within the Navarrese cohort, with 35% classified as common (MAF &gt; 1%). By comparing allele frequency data from 1000 Genome Project (excluding the Iberian cohort of Spain, IBS), Genome Aggregation Database, and a Spanish cohort (including IBS individuals and data from Medical Genome Project), we identified 1069 SNVs common in Navarre but rare (MAF ≤ 1%) in all other populations. We further corroborated this observation with a second regional cohort of 239 unrelated exomes, which confirmed 676 of the 1069 SNVs as common in Navarre. In conclusion, this study highlights the importance of population-specific characterization of genetic variation to improve allele frequency filtering in sequencing data analysis to identify disease-causing variants.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Díez-Fuertes, F</style></author><author><style face="normal" font="default" size="100%">De La Torre-Tarazona, H E</style></author><author><style face="normal" font="default" size="100%">Calonge, E</style></author><author><style face="normal" font="default" size="100%">Pernas, M</style></author><author><style face="normal" font="default" size="100%">Bermejo, M</style></author><author><style face="normal" font="default" size="100%">García-Pérez, J</style></author><author><style face="normal" font="default" size="100%">Álvarez, A</style></author><author><style face="normal" font="default" size="100%">Capa, L</style></author><author><style face="normal" font="default" size="100%">García-García, F</style></author><author><style face="normal" font="default" size="100%">Saumoy, M</style></author><author><style face="normal" font="default" size="100%">Riera, M</style></author><author><style face="normal" font="default" size="100%">Boland-Auge, A</style></author><author><style face="normal" font="default" size="100%">López-Galíndez, C</style></author><author><style face="normal" font="default" size="100%">Lathrop, M</style></author><author><style face="normal" font="default" size="100%">Dopazo, J</style></author><author><style face="normal" font="default" size="100%">Sakuntabhai, A</style></author><author><style face="normal" font="default" size="100%">Alcamí, J</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Association of a single nucleotide polymorphism in the ubxn6 gene with long-term non-progression phenotype in HIV-positive individuals.</style></title><secondary-title><style face="normal" font="default" size="100%">Clin Microbiol Infect</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Clin Microbiol Infect</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adaptor Proteins, Vesicular Transport</style></keyword><keyword><style  face="normal" font="default" size="100%">Autophagy-Related Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Caveolin 1</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Dendritic Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Disease Progression</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Frequency</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Knockdown Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Association Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">HeLa Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">HIV Infections</style></keyword><keyword><style  face="normal" font="default" size="100%">HIV Long-Term Survivors</style></keyword><keyword><style  face="normal" font="default" size="100%">HIV-1</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Macrophages</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">whole exome sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">26</style></volume><pages><style face="normal" font="default" size="100%">107-114</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;OBJECTIVES: &lt;/b&gt;The long-term non-progressors (LTNPs) are a heterogeneous group of HIV-positive individuals characterized by their ability to maintain high CD4 T-cell counts and partially control viral replication for years in the absence of antiretroviral therapy. The present study aims to identify host single nucleotide polymorphisms (SNPs) associated with non-progression in a cohort of 352 individuals.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;DNA microarrays and exome sequencing were used for genotyping about 240 000 functional polymorphisms throughout more than 20 000 human genes. The allele frequencies of 85 LTNPs were compared with a control population. SNPs associated with LTNPs were confirmed in a population of typical progressors. Functional analyses in the affected gene were carried out through knockdown experiments in HeLa-P4, macrophages and dendritic cells.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Several SNPs located within the major histocompatibility complex region previously related to LTNPs were confirmed in this new cohort. The SNP rs1127888 (UBXN6) surpassed the statistical significance of these markers after Bonferroni correction (q = 2.11 × 10). An uncommon allelic frequency of rs1127888 among LTNPs was confirmed by comparison with typical progressors and other publicly available populations. UBXN6 knockdown experiments caused an increase in CAV1 expression and its accumulation in the plasma membrane. In vitro infection of different cell types with HIV-1 replication-competent recombinant viruses caused a reduction of the viral replication capacity compared with their corresponding wild-type cells expressing UBXN6.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;A higher prevalence of Ala31Thr in UBXN6 was found among LTNPs within its N-terminal region, which is crucial for UBXN6/VCP protein complex formation. UBXN6 knockdown affected CAV1 turnover and HIV-1 replication capacity.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31158522?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gómez-López, Gonzalo</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Cigudosa, Juan C</style></author><author><style face="normal" font="default" size="100%">Valencia, Alfonso</style></author><author><style face="normal" font="default" size="100%">Al-Shahrour, Fátima</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Precision medicine needs pioneering clinical bioinformaticians.</style></title><secondary-title><style face="normal" font="default" size="100%">Brief Bioinform</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Brief Bioinform</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Precision Medicine</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 May 21</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">752-766</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Success in precision medicine depends on accessing high-quality genetic and molecular data from large, well-annotated patient cohorts that couple biological samples to comprehensive clinical data, which in conjunction can lead to effective therapies. From such a scenario emerges the need for a new professional profile, an expert bioinformatician with training in clinical areas who can make sense of multi-omics data to improve therapeutic interventions in patients, and the design of optimized basket trials. In this review, we first describe the main policies and international initiatives that focus on precision medicine. Secondly, we review the currently ongoing clinical trials in precision medicine, introducing the concept of 'precision bioinformatics', and we describe current pioneering bioinformatics efforts aimed at implementing tools and computational infrastructures for precision medicine in health institutions around the world. Thirdly, we discuss the challenges related to the clinical training of bioinformaticians, and the urgent need for computational specialists capable of assimilating medical terminologies and protocols to address real clinical questions. We also propose some skills required to carry out common tasks in clinical bioinformatics and some tips for emergent groups. Finally, we explore the future perspectives and the challenges faced by precision medicine bioinformatics.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/29077790?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Corton, M</style></author><author><style face="normal" font="default" size="100%">Avila-Fernández, A</style></author><author><style face="normal" font="default" size="100%">Campello, L</style></author><author><style face="normal" font="default" size="100%">Sánchez, M</style></author><author><style face="normal" font="default" size="100%">Benavides, B</style></author><author><style face="normal" font="default" size="100%">López-Molina, M I</style></author><author><style face="normal" font="default" size="100%">Fernández-Sánchez, L</style></author><author><style face="normal" font="default" size="100%">Sánchez-Alcudia, R</style></author><author><style face="normal" font="default" size="100%">da Silva, L R J</style></author><author><style face="normal" font="default" size="100%">Reyes, N</style></author><author><style face="normal" font="default" size="100%">Martín-Garrido, E</style></author><author><style face="normal" font="default" size="100%">Zurita, O</style></author><author><style face="normal" font="default" size="100%">Fernández-San José, P</style></author><author><style face="normal" font="default" size="100%">Pérez-Carro, R</style></author><author><style face="normal" font="default" size="100%">García-García, F</style></author><author><style face="normal" font="default" size="100%">Dopazo, J</style></author><author><style face="normal" font="default" size="100%">García-Sandoval, B</style></author><author><style face="normal" font="default" size="100%">Cuenca, N</style></author><author><style face="normal" font="default" size="100%">Ayuso, C</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identification of the Photoreceptor Transcriptional Co-Repressor SAMD11 as Novel Cause of Autosomal Recessive Retinitis Pigmentosa.</style></title><secondary-title><style face="normal" font="default" size="100%">Sci Rep</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Sci Rep</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Co-Repressor Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Codon, Nonsense</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Comparative Genomic Hybridization</style></keyword><keyword><style  face="normal" font="default" size="100%">Consanguinity</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Mutational Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Eye Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Recessive</style></keyword><keyword><style  face="normal" font="default" size="100%">Homeodomain Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Homozygote</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Interaction Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">Retina</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinal Dystrophies</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinal Rod Photoreceptor Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinitis pigmentosa</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword><keyword><style  face="normal" font="default" size="100%">Trans-Activators</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Oct 13</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">35370</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Retinitis pigmentosa (RP), the most frequent form of inherited retinal dystrophy is characterized by progressive photoreceptor degeneration. Many genes have been implicated in RP development, but several others remain to be identified. Using a combination of homozygosity mapping, whole-exome and targeted next-generation sequencing, we found a novel homozygous nonsense mutation in SAMD11 in five individuals diagnosed with adult-onset RP from two unrelated consanguineous Spanish families. SAMD11 is ortholog to the mouse major retinal SAM domain (mr-s) protein that is implicated in CRX-mediated transcriptional regulation in the retina. Accordingly, protein-protein network analysis revealed a significant interaction of SAMD11 with CRX. Immunoblotting analysis confirmed strong expression of SAMD11 in human retina. Immunolocalization studies revealed SAMD11 was detected in the three nuclear layers of the human retina and interestingly differential expression between cone and rod photoreceptors was observed. Our study strongly implicates SAMD11 as novel cause of RP playing an important role in the pathogenesis of human degeneration of photoreceptors.&lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/27734943?dopt=Abstract</style></custom1></record></records></xml>